Private, local SMS spam filtering — built by Dro1d Labs.
Defndr processes messages entirely on-device, providing high-accuracy SMS spam detection without sending any data off the device.
Defndr is live on the iOS App Store.
Official site: https://defndr.org
Research: https://dro1d.org/defndr
This repository provides reference implementations for:
- Deterministic SMS preprocessing
- Hybrid spam scoring combining heuristics and ML
- On-device monitoring of model performance
- High-performance architecture for iOS 17/18+
It does not include the proprietary filtering model or pipeline.
Tokenization, normalization, and deterministic preprocessing of SMS text.
Combines heuristics and ML scoring for spam classification.
Monitors model performance and drift entirely on-device.
- All code, models, and data are Dro1d Labs intellectual property.
- No copying, redistribution, or commercial use without explicit written permission.
flowchart LR A[Raw SMS] --> B[MessagePreprocessingPipeline] B --> C[Heuristics + ML Vote] C --> D[HeuristicSignalScoring] D --> E[Block / Allow Decision]
License: Educational and reference purposes only. No commercial use, modification, or redistribution permitted without explicit written permission from Dro1d Labs.
🧭 Stay Updated: https://defndr.org